Experiments.
We first created explanations for the same data point following the methods of LIME, SHAP and SAT, which are described in detail next.
LIME  [1]} provides local explanations of model predictions global by creating an approximation near the input. Feature importance can be inferred from this local linear approximation by looking at the feature weights. For our experiments, we mirrored the feature importance experiments of the LIME repositoryhttps://github.com/marcotcr/lime.
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